SynthesisBMC health services research2024
The integration of human and non-human actors to advance healthcare delivery: unpacking the role of actor-network theory, a systematic literature review.
Synthesis in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- An exploration of the concept and practice of patient-centered care in medical education in Pakistan.Pakistan journal of medical sciences · 2026Article
- Living with a robot at home: the complexity of living with assistive robots in everyday life.Frontiers in dementia · 2026Article
- Public Health Risk Management, Policy, and Ethical Imperatives in the Use of AI Tools for Mental Health Therapy.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is an increasing public, societal and policy imperative for effective integration of healthcare delivery systems. Central to integration in healthcare is a focus on people-centred health, access, patient empowerment, interprofessional teamwork and collaboration between all healthcare stakeholders - difficult to achieve in current silo-driven bureaucratic health organisations. Therefore, actor-network theory (ANT) offers a theoretical approach to understanding the complexities of healthcare delivery by unpacking the type of actor's interplay between social elements and immaterial objects, their interactions, interdependencies and power dynamics.
aimsThe first of its type, this systematic review aims to identify, synthesise, and appraise extant literature on the use and application of ANT in healthcare contexts.
methodsThis systematic review was conducted in accordance with PRISMA guidelines and registered with PROSPERO. The authors generated a search strategy utilising 31 Boolean terms, conducting electronic searches of MEDLINE, CINAHL Complete, SCOPUS, PubMed, APA PsycINFO, Business Source Complete and Academic Search Complete. The studies obtained were evaluated for inclusion based on their alignment with the specified inclusion and exclusion criteria. Studies were independently evaluated by the authors, with all data synthesised using a thematic analysis.
resultsFrom an initial 2,533 studies, the systematic review included 103 studies which utilised ANT within a healthcare context. The analysis of the studies identified trends in the application of ANT across healthcare which we categorised into four themes: healthcare delivery systems, technology and data, integrated care, and innovation management. The findings demonstrated variability and fragmentation in the application of ANT, often diverging from its fundamental principles.
conclusionsDecluttering the literature suggests three dimensions for understanding the relationships of actors, unidimensional ANT - based on single actors, bi-dimensional ANT, the relationship between two actors and multi-dimensional ANT, where human and non-human actors interact to impact healthcare outcomes. The limited number of studies on the use of ANT for integrated healthcare research highlights both its importance to the topic and the considerable research gap that must be addressed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.